Journal of Environmental Protection, 2016, 7, 1670-1692 http://www.scirp.org/journal/jep

ISSN Online: 2152-2219 ISSN Print: 2152-2197

DOI: 10.4236/jep.2016.711136 October 31, 2016

Relationship between the Environment and Economic Growth in China via Exports: A Perspective of Ecological Impact (2000-2014)

Guillermo Velázquez Valadez1, Jiaqi Hu2

1La Salle University; SEPI-ESE IPN, Mexico City, Mexico 2Economics Program SEPI- ESE-IPN, PHD in Economics of ESE-IPN, Mexico City, Mexico

Abstract China’s swift and substantial economic growth over the past 20 years has made the country one of the top industrial powers in the world, second only the United States. From the perspective of ecology and the impact on the environment produced by economic and industrial growth, the exports that have driven rapid growth have also resulted in an alarming level of environmental pollution in major Chinese cities. Re-search has shown that the Chinese government’s investment in bringing down pollu-tion levels has been insufficient and ineffective. The monetary amount allocated for pollution reduction has barely reached 0.15% of the country’s GDP and has failed to meaningfully reverse the effects of industrialization, including increased exports and economic growth rates affecting China’s ecology. The present study investigated China’s ecological situation in terms of the industrial production that has generated its level of exports, with special focus on problems related to water, air, and solid waste. An econometric analysis was conducted to determine the relationship between the main variables. The exports and GDP (dependent variable), air pollution, water pollution, and industrial solid waste (independent variables) were provided by the Institute of Statistics and the Environment Institute of China for this study. The data was managed in Econometric Eviews 7.0 software and yielded an adjusted R2 of 96.09% (high correlation) with an interesting correlation between the exports and three independent variables; after subsequent variable analysis, we found that in-vestments in water and industrial solid waste were not significant (i.e., that said in-vestments have failed to solve the pollution problem). It is necessary to review the Chinese investment policy with special attention to these variables to appropriately respond to China’s ecological crisis.

How to cite this paper: Valadez, G.V. and Hu, J.Q. (2016) Relationship between the Environment and Economic Growth in China via Exports: A Perspective of Ecolog-ical Impact (2000-2014). Journal of Envi-ronmental Protection, 7, 1670-1692. http://dx.doi.org/10.4236/jep.2016.711136 Received: September 26, 2016 Accepted: October 28, 2016 Published: October 31, 2016 Copyright © 2016 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/

Open Access

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Keywords Economic Growth, Environment, Exports; Pollution, Gross Domestic Product

1. Introduction

China is one of thirteen countries worldwide contending with a serious water scarcity problem. Over the course of the next twenty years, the country has plans to ensure economic and social development to mitigate this problem. It is worth noting here that per capita water resources in China are 2300 cubic meters, representing a quarter of the world’s average. The water problem has caused a series of deficiencies in the production of the two main sectors of the economy: Industry, at a loss of $46 billion (USD) and agriculture at $30 billion in 2014. Moreover, soil erosion and the continued reduction of arable land are becoming increasingly serious. Soil erosion has reached 2949 square kilometers according to the Bulletin of the Environment of China (2014), a figure equivalent to 30% of the national surface. In effect, annual land disappearance by ero-sion is equivalent to ten times the surface area of Japan. It is difficult to account for the economic damage caused by such drastic environmental changes. In 2014, soil cultiva-tion in China was 135,163,000 hectares—an average of arable land less than half the world’s average and the loss of cultivated land was 354,000 hectares in the same year.

Air pollution costs China $30 billion dollars (BBC) annually and has resulted in the premature death of more than 500,000 people in last ten years. Respiratory diseases and cardiovascular and lung cancers due to pollution are increasing 26.9% annually (CENEWS) since 2000; in other words, every minute there are six individuals diag-nosed with a disease caused by pollution: 8550 per day, and 3.12 million per year. The level of suspended particle micro-density is 300 - 370 units per cubic meter, which places China squarely and constantly under yellow alert on the Air Quality Index (AQI) of China during last fifteen years. The country currently has 62,000 industrial coal boi-lers, consumes 700 million tons of coal in 2014, and has no adequate pollutant control measures in place. It is projected that by 2020, China will need 4.2 billion tons of coal, certainly a dire situation in terms of air quality.

Among the most hazardous industrial wastes produced in China is the ash emitted during the burning of coal. For every four tons of coal consumed, one ton of ash is re-leased into the atmosphere. It is important to note that in both 2002, when coal burning increased significantly, and again in 2009, ash production reached 375 million tons per year—this is equivalent to more than twice the total production of trash by Chinese metropolitan areas that year (Greenpeace).

2. Objectives

Our primary objective was to perform an econometric analysis between economic growth and the factors that impact environmental pollution in China by way of its ex-ports, particularly industrial exports, during the period 2000-2014.

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3. Hypothesis

During the last fourteen years, the Chinese economy (measured here in terms of Gross Domestic Product [GDP]) has grown at an average annual rate of 7% to 8%. The con-sequences of such economic growth, as often discussed in terms of the consumption of raw materials, also include a significant increase in pollution. New industrial policy measures and environmental sustainability legislation are urgently necessary in order to sustain the Chinese growth model over the next 15 years.

4. Theories of Economic Growth versus Sustainable Growth

Economic growth and sustainable growth are topics of discussion that have caused de-bates and clashes among intellectual circles that support different and contending theo-ries as they relate to ecology and the environment. In this sense, it is essential to identi-fy the main theories that support the industrialization process of China.

4.1. Economic Growth

Nicholas Kaldor (1963) established the typical factors that drive economic growth and generate accelerated production. These factors include:

1. Continuous growth in the total volume of production and labor productivity at a rate of a consistent trend. 2. Increased amount of capital per worker. 3. Constant rate of capital gains. 4. Foreign capital-output that is stable for long periods of time. 5. High correlation between the share of profits in income and the share of invest-ment in production. 6. Appreciable differences in the rate of growth of labor productivity and total pro-duction indifferent societies.

Kuznets [1] [2] and Romer (1989) [3] have defined economic growth as “a long- term increase in the supply capacity of more diverse economic goods to its popula-tion, the growing ability based on the advancement of technology and institutional and ideological adjustments that demand”. They have also pointed out additional factors that directly impact economic growth and are used by governments to make their economies more productive. These include low gradual dependence on natural resources, increasing importance of government sector in the economy, and an in-crease in the importance of formal education reflected in the economy.

Birdsall and Wheeler [4], Lee and Ronal-Holst [5], and Jones and Rodolfo [6] all have indicated that in theory, foreign trade has an effect on economic expansion proportionate to expansion in production(especially industrial) as a result of exter-nal demands for products and services; that is, these economic activities have a di-rect impact on pollution. Foreign trade also results in decomposition, which must be understood as the decline of the great centers of world production due to migra-tion to other countries with comparative advantages over the country of origin; this serves to increase the foreign trade between countries, but also spreads and increas-

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es pollution, known as the “Pollution Haven Hypothesis”. Kuznet (1973) further contends that the effect of decomposition is actually the migration of contamina-tion. Developed countries produce products with less pollution whereas emerging countries produce them with high energy consumption [7]. Rock confirms this statement: “If there is no strict environmental regulation under the neoliberal model and free trade, then the industries increase their rate of migration from developed countries to developing countries” [8] [9].

4.2. Sustainable Growth

Ramsey and Koopmans [10] and Cass [11] together developed a dynamic optimiza-tion model which has been used by many economists to study the optimal use of natural resources and analysis of economic trajectory. Pollution is also introduced as a variable within the Ramsey-Cass-Koopmans model to show the relationship between long-term economic growth and environmental pollution.

Keeler, Spence, and Zeckhuaster (2001) indicate that the integration of the pollution variable into models of economic growth should be considered if any of the three following scenarios is true: First, if contamination has a direct impact on consump-tion, production or possibly both, in which case contamination enters directly into the social utility function with a negative marginal utility; second, if contamination is perceived as an act of economic agents or as a flow of production processes; and third, if contamination is the result of different economic models, then the result and assumptions are different.

Beckerman [12] argues that concurrent with economic growth, demand for envi-ronmental quality will inevitably lead to an increase in more stringent environmen-tal protection measures. The strong correlation between income and the extent to which environmental protection measures are taken shows that frankly, in the long run, the best way to improve the environment is by becoming wealthy. In this con-text, one can say that the development of the economy increases income and envi-ronmental quality parameters, which leads to a structural change in production, distribution, and consumption. This period of economic growth is based on man-agement, innovation, technology, and productivity–variables that allow more in-come for businesses and families which to be spent on the purchase of equipment for environmental protection, thereby enforcing regulations that result in ecological balance. Such situations can have the following three effects:

1. Composition effect: Countries with developed economies base their economy on the service sector. Under these conditions, the demand for inputs is serviced by devel-oping countries. The agricultural sector cedes its space to the industrial sector, and de-veloped countries thus pollute emerging countries by way of transference of industrial processes.

2. Displacement effect: Based on the principles of neoliberal capitalism, globalization interacts with increased international flow of goods and, based on the increased inter-national division of labor, developed countries are released from polluting industrial

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processes and move them instead to developing countries. 3. Technological progress: This effect is perceived as positive because, in so far as the

economy grows; countries are able to invest in research around development and pos-sibilities for improving technology which can then be applied to overcome the effects of pollution on the environment.

4.3. Theoreticians of Foreign Trade and Pollution (China)

Zoran Xie and Zong Gang [13] [14] [15] discussed the issue of socio-economic sur-pluses or internalization of environmental costs that impact the process of global pollution; they indicate that China should promote the growth of foreign trade ba-lanced with sustainable economic growth based on technological progress, man-agement of new raw materials friendly to the environment, and increased regula-tions to control and promote openness to environmental businesses and reduce negative external effects.

Yu Yonghong [16] [17] noted that international trade disputes about the environ-ment are a result of different interests and regulatory standards between developed and developing countries. Yonghong proposed efficient legal solutions for sustaina-ble development accordingly.

Huang and Li [18] emphasized that high levels of economic growth required of de-veloping countries cause conflicts between international trades. The solution, ac-cording to these scholars, is to increase investment in these countries in the devel-opment of human capital as well as enhance their active participation in interna-tional trade negotiations and generate unique standards to be observed by all in re-gards to environmental regulations.

Ye and Xu [19] [20] [21] [22] found that most of the industries operating in the field of exports are industries that generate high levels of contamination; they argued that industries must avoid competition between exports and the limits set by the environ-ment in the exploitation of natural resources and their subsequent industrialization.

Dang Yuting [23] found that foreign trade reduces pollution (especially in the man-ufacturing sector) mainly due to the constant technological progress in developed countries.

Yu Lixin [24] contended that more than 80% of existing pollution is caused by the constant emission of gaseous and solid industrial waste from industrialized coun-tries, which is why these countries should not impose or punish pollution in under-developed countries. The carbon emission quota seriously affects China’s foreign trade and, as such, China must develop its own technology to achieve sustainable growth.

5. Exports and Pollution in China

During the past twenty years, China has demonstrated swift and substantial economic growth: Its GDP has increased by an annual average of 14.98%, representing economic dynamism that now makes China the third largest economy in the world, topped only by the European Union (EU) and the United States (US). In the same period, China’s

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exports have increased by an annual average of 16.43%.These figures are important be-cause they indicate that China’s expansion in foreign markets is higher than its own rate of growth. It is estimated that if this trend continues, in 2030, China will rank as the world’s largest economy (Chinese Embassy in Jamaica, 2015).

The role of exports in GDP growth has been increasing steadily, as well: In 1995, ex-ports represented 20.8% of the GDP as compared to 22.9% in 2014. The percentage of exports to GDP peaked between 2004 and 2008 at greater than 30%. Figures expressing this data are presented below (Table 1).

The relationship between GDP-China Export variables (measured in millions of dol-lars) from 2000 behave correlatively, as represented in the following graph (Figure 1).

It is important to note that 49.2%, i.e., almost half of China’s GDP can be attributed to foreign trade (Export-Import). Another 26.4% can be attributed to exports; within this category, exports of industrial finished products constitute more than 96% and re-sult in an annual growth rate of 18% on average. In other words, Chinese exports are concentrated in industrial products; accordingly, the growth of industrial clusters and corridors are very high (Figure 2). Table 1. Exports Percentage of GDP of China from 1995 to 2014.

Year Percentage Year Percentage Year Percentage Year Percentage 1995 20.8 2000 21.1 2005 33.9 2010 26.7 1996 17.9 2001 20.4 2006 36.0 2011 26.5 1997 19.4 2002 22.6 2007 34.9 2012 24.9 1998 18.3 2003 26.9 2008 32.0 2013 23.3 1999 18.2 2004 30.8 2009 24.1 2014 22.9

Based on data from the National Institute of Statistics of China.

Figure 1. GDP growth and export in China from 1995 to 2014. Source: Prepared with data from the National Institute of Statistics of China.

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Figure 2. China Total exports and. Exports of Industrial Products 1995-2014. Based on data from the National Institute of Statistics of China.

As shown in the chart above, exports of finished industrial products clearly main-tained a high share of total exports during the period we examined. This steady growth trend has implications for the country as a whole in terms of consumption of energy, exploitation of raw materials, and pressure for environmental regulations.

The industrial composition is divided into four areas each with a certain annual av-erage participation. Chemicals constitute 6% Light industry, 19% Machinery and equipment, 45% Other products, 30%

Based on the above composition, exports of machinery and equipment present a high dynamism: Their share of industrial composition has increased from 24% in 1995 to 45% in 2014, meaning that China has extensively developed technology and its own brand of exports to the world. As a result, industry shows a slight decrease of 5% in their share of the GDP in the same period; the share of chemicals to GDP has remained the same.

The curve relating to finished industrial products shown in Figure 3 indicates that since 2000, China has significantly increased its industrial exports at a rate disturbed only by the global crisis of 2008-2009. The curve, however, also shows a recovery of the industrial sector—and an even greater growth rate—starting in 2010. The curve for the

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Figure 3. Based on data from the National Institute of Statistics of China. machinery and equipment category shows a similar trend, i.e., it is another of the fast-est-growing categories that comprise China’s industrial composition [25].

The data presented above indicates positive economic consequences for China, but it is certainly necessary to conduct a deeper analysis into the other side of the accelerated industrialization: The ecological effects and the industrial sector’s own level of respon-sibility for (and impact on) environmental pollution.

6. Air Pollution

A visible effect of accelerated industrialization for the Chinese population is the high air pollution experienced mostly in larger cities, especially Beijing. This situation has led the government to enact strong measures and restrictions in effort to control the envi-ronmental contingency. In this context, and due to the alarming increase in pollution levels, the National Institute of Statistics of China in 2011 was forced to expand the classification of air pollution and industrial emissions SO2 and NO2 to air pollution. These emissions are currently responsible for 88% and 67% of total Chinese air pollu-tion, respectively (National Statistical Bulletin of China Environment, 2014).

As shown in Table 2, the emission of 115.59 million tons of air pollutants in 2011 decreased to 113.06 million tons in 2014, which, in relative terms, represents a decrease of only 2.1% of the total emissions. Table 1 also shows that by 2014, weightier pollu-tants were present in the environment: Sulfur dioxide represented 17.46% of total emis-sions while nitrogen oxide represented 21.25% of the emissions.

Importantly, micro particles suspended in the air have increased significantly from 2011 to 2014: Micro Part Susp + Fumes increased from 12.78 million tons in 2011 to 17.40 million tons in 2014, which is an increase of 36.15% (4.62 million tons) in just four years. In the case of Indus + Smoke Indus Micro, the increase was from 11.00 mil-lion tons in 2011 to 14.56 million tons in 2014, i.e., an increase of 32.36% (3.56 million tons) in the same period. This increase in emitted particles is mainly due to the high demand for energy by industries and is generated by burning coal [26].

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Table 2. Air pollution (million tons).

Year Sulfur

dioxide INDUS DIXO

Nitrogen oxides

NITRO INDUS

NITRO by CAR

Micro Particle

Susp + Smock

Micro indus + Smock

Indus

Micro Particle

Domestic

Micro particle by car

2011 22.17 20.17 24.04 17.29 6.37 12.78 11.00 1.14 0.629

2012 21.17 19.11 23.37 16.58 6.40 12.34 10.29 1.42 0.620

2013 20.43 18.35 22.27 15.45 6.40 12.78 10.94 1.23 0.594

2014 19.74 17.40 20.78 14.05 6.28 17.40 14.56 2.27 0.574

Source: Statistical Yearbook of China National Institute of Environment of China. Note: there are no reliable data for the years 1995-2010.

7. Water Pollution

The current situation regarding the degree of water pollution in China is alarming not only in regards to human consumption, which is paramount, but also for irrigation in food production and water consumption by different types of livestock which provide meat to be consumed in the country. In this sense, water pollution is a doubly serious problem–primarily because government costs must rise in order to combat the different diseases that occur from water consumption, and secondly because it raises the import of pollution-free food, which affects mainly lower income classes (Figure 4).

Although biological oxiation by refractories is non-biodegradable (by conventional methods,) residual waste present in aqueous streams are mainly industrial. These con-taminants also appear in lesser domestic concentrations. Present in this type of pollu-tion are polynuclear aromatic hydrocarbons (PAH), phenolic compounds, halogenated hydrocarbons (AOX), BTEX, pesticides, and dyes, all of which can be grouped under the “refractory COD” category which includes the organic load (Table 3).

Water pollution in China between 2002 and 2014 increased at an average rate of 5.24% annually, representing an increase of 27.670 million tons of pollutants dis-charged into rivers, lakes, and lagoons. In terms of percentage, the increase of conta-minants was approximately 162.95%. It is worth emphasizing that the COD parameter in wastewater emissions increased from 13.55 million tons in 2002 to 22.94 million tons in 2014, i.e., an increase of 167.93% over the course of the period we examined in this study.

8. Industrial Waste

Industrial waste is a category that originated during the Industrial Revolution in the late nineteenth century to represent waste produced by humans through industrial ac-tivity. Industrial wastes are classified as hazardous or inert. Inert wastes, such as debris and sand, are typically recoverable although the majority of such waste ultimately ends up in open dumps; its main effect is a visual pollution. Hazardous waste, on the other hand, can affect human, plant, and animal health, i.e., the environment at large. Ha-zardous waste is toxic, corrosive, can be plastic (or many other non-biodegradable ma-terials) and is not easy to reuse insofar as they typically require lengthy periods to de-grade when discarded in nature or landfills.

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Figure 4. Source: Statistical Yearbook of China National Institute of Statistics of China. Note: there are no reliable data for the years 1995-2001. Table 3. Water pollution (million tons).

Year Total Industrial pollution

Domestic use

COD in wastewater emissions

Ammonia residues

Industrial COD

Industrial ammonia

2002 43,950 20,720 23,230 13.66 1.28 5.84 0.421

2003 46,000 21,240 24,760 13.33 1.29 5.12 0.404

2004 48,240 22,110 26,130 13.39 1.33 5.09 0.422

2005 52,450 24,310 28,140 14.14 1.49 5.54 0.525

2006 53,680 24,020 29,660 14.28 1.41 5.41 0.425

2007 55,680 24,660 31,020 13.81 1.32 5.11 0.341

2008 57,170 24,170 33,000 13.20 1.27 4.57 0.297

2009 58,970 23,450 35,520 12.78 1.22 4.40 0.273

2010 61,730 23,750 37,980 12.38 1.23 4.34 0.273

2011 65,920 23,090 42,790 24.99 2.60 3.54 0.281

2012 68,480 22,160 46,270 24.23 2.53 3.38 0.264

2013 69,544 20,984 48,511 23.53 2.46 3.19 0.246

2014 71,620 20,530 51,030 22.94 2.32 3.11 0.232

Based on data from the National Institute of Statistics of China. COD: Chemical Oxygen Demand.

The high rates of economic growth (again, driven mainly by exports,) that industrial

China experienced between 1995 and 2014 can help explain the considerable increase in pollution in the country. In 1995, a total of 644.74 million tons of industrial waste was recorded in 2014, which number grew to 3526.21 million tons, reflecting an increase of 546.91% (Table 4).

Another important problem that China must address is that until 2014, 100% of in-dustrial waste had a utilization of 57.95% and a storage of 12.77%; together these fig-ures amount to 70.72%, meaning that 29.28% of industrial waste is not accounted for and, therefore, neither its final destination nor the degree of pollution it produced (Figure 5).

The calculation of total emissions (in millions of tons) in 2014 can be visually represented as follows (Table 5).

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Figure 5. Pollution composition of China 2014. Source: Statistical Yearbook of China National Institute of Statistics of China. Table 4. China industrial waste in 1995-2014 (million tons).

Year Total Exploitation Storage

1995 644.74 285.11 247.79

1996 658.98 283.65 363.64

1997 1058.49 427.77 299.12

1998 800.68 333.87 275.46

1999 784.41 357.55 262.94

2000 816.07 374.51 289.21

2001 887.45 472.85 301.66

2002 945.05 500.61 300.39

2003 1004.28 560.40 276.67

2004 1200.31 677.95 260.11

2005 1344.48 769.93 278.76

2006 1515.41 926.01 223.98

2007 1760.10 1103.11 241.19

2008 1900.12 1234.81 218.82

2009 2040.14 1381.85 209.29

2010 2410.11 1617.72 239.18

2011 3227.72 1952.15 604.24

2012 3290.44 2024.62 597.86

2013 3277.02 2059.16 426.34

2014 3526.21 2043.30 450.33

Based on data from the National Institute of Environment of China.

Table 5. Pollution quantity composition of China 2014.

Category Millions of tons Percentage

Water pollution 71,620.00 95.16

Air pollution 113.059 0.15

Industrial waste pollution 3526.21 4.69

Total 75,259.27 100.00

Self-elaboration based by National Institute of Environment of China.

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It is clear that water pollution is the main source of contamination in China insofar as it directly affects the soil, thereby negatively impacting agricultural and livestock products. Moreover, the increasing scarcity of national reserves of drinking water threatens the viability of Chinese cities. Between 1995 and 2014, the amount and level of water contamination (measured in percentages) has remained virtually the same, re-gardless of efforts made by way of legislation, new technologies, or environmental or-ganizations.

9. Econometric Model

In order to test the relationship between exports and figures of water and air contami-nation and solid industrial waste, we proceeded to perform an econometric analysis. Our goal was to determine whether the government has adequately responded to the level of severity of the pollution situation in China.

9.1. Methodology

After gathering materials and articulating a scheme of scientific research elements, we conducted documentary research into the growth of China in terms of both the GDP and Chinese exports. We then built a theoretical framework accordingly. Our research can be defined as descriptive-correlational, as it consists of examining statistical and econometric analyses in order to find a correlation between exports and pollution in China.

We also gathered data regarding water pollution, air pollution, and industrial solid waste and evaluated these effects as they relate to China’s high rate of industrial growth. We found that although economic growth in this country has been positive in the last twenty years, pollution levels have risen alarmingly. In response to this situation, we propose a correlational model through which we can establish a number of variables: “Exports”, “Air pollution”, “Water pollution”, and “Industrial solid waste”. These va-riables were incorporated into the following Model:

Dependent Variables Independent Variable

EXP = Exports

CAI = Air Pollution Investment CAG = Water pollution Investment DSI = Industrial Waste Investment

C= Constant term of regression

The model was formulated as follows:

EXP CAI CAG DSI C= + + +

With the data collected and the model designed, we proceeded to perform our eco-nometric analysis in EViews software, which is especially useful for analysis of cross- sectional models, estimation and prediction models, time series, and panel data. The data collected by the software were analyzed and interpreted in order to arrive at con-clusions that were supported by mathematical coefficients. This provided the necessary

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confidence that a scientific study demands, and allowed for the criteria of acceptance or rejection of the hypothesis.

In order to secure homogeneous data (Table 6), all variables taken from the current Statistical Yearbook of the National Institute of Statistics of China were expressed in millions of dollars [27] [28].

After running the above data through EViews software based on our correlational model, we found that under the LS (Least Squares) method and ARMA, when the in-dependent Exports variable and dependent variables Investments in Air, Water, and Waste were individually tested, all variables passed. The individual results are presented below.

Variable R2 P t F DW ARMA Result

Air 0.755 0.0000 10.21 52.6 0.56 OK

Water 0.9806 0.0167 10.16 404.38 2.61 1 OK

Waste 0.4455 0.0013 8.06 14.46 0.72 Weak

Table 6. China: Total investment in environment vs. Total investment in industrial pollution (Millions of dollars).

Year Total

environment investment

Industrial pollution control

Investment

Industrial solid waste control investment

Air pollution control

investment

Water pollution control

Investment 1995 1181.94 714.91 168.85 0 546.06

1996 1149.84 447.43 109.45 0 337.98

1997 1404.60 1300.67 76.10 346.49 878.08

1998 1495.33 1383.00 105.08 392.55 885.36

1999 1841.88 1547.18 100.25 615.97 830.96

2000 12,812.86 2836.17 138.52 1098.33 1323.80

2001 13,369.58 2108.59 225.89 794.90 881.01

2002 16,472.15 2275.78 194.86 843.14 863.76

2003 19,659.55 2679.92 195.43 1112.94 1055.58

2004 23,056.29 3721.99 273.57 1725.02 1275.51

2005 29,198.87 5602.45 335.25 2603.90 1634.97

2006 32,039.03 6038.34 227.87 2910.56 1885.51

2007 44,501.66 7256.56 239.79 3616.05 2575.73

2008 63,549.77 7679.82 278.60 3760.35 2754.08

2009 66,237.30 6186.07 319.88 3402.64 2187.72

2010 98,532.57 5878.61 211.75 2795.67 1935.35

2011 92,836.14 6805.51 480.86 3241.96 2415.01

2012 130,801.90 7931.85 391.44 4083.99 2223.45

2013 145,921.33 13,719.24 226.86 10348.61 2016.41

2014 154,031.14 16,048.97 242.90 12843.03 1853.10

TOTAL 950,093.75 102,163.05 4543.20 56,536.10 30,359.45

Based on data from the National Institute of Statistics of China.

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By examining the relationship between pollutants, exports, and investments, we gen-erated a model that supports the continued good performance of exports with the im-plementation of sound public policy. We also observed a strong correlation between exports and investments to combat pollution in water (98.06%), while the ratio of ex-ports to waste is very low (44.55%). In effect, then, there is an imbalance in government investment in fighting pollution.

( )EXPORT 151.303575255 AIR 332.50858122 Water

443.520012548 Waste 230696.415895 AR 20.0120454075199

= ∗ + ∗

+ ∗ − +

= −

Dependent Variable: EXPORT

Method: Least Squares

Date: 04/06/16 Time: 22:29

Sample (adjusted): 1997 2014

Included observations: 15 after adjustments

Convergence achieved after 7 iterations

Variable Coefficient Std. Error t-Statistic Prob.

AIR 151.3036 21.76482 6.951751 0.0000

WATER 332.5086 61.47551 5.408797 0.0003

WASTE 443.5200 450.3745 0.984780 0.3480

C −230696.4 91090.19 −2.532615 0.0297

AR(2) −0.012045 0.271572 −0.044354 0.9655

R-squared 0.988635 Mean dependent var 837,924.8

Adjusted R-squared 0.984089 S.D. dependent var 718,241.1

S.E. of regression 90,597.36 Akaike info criterion 25.92744

Sum squared resid 8.21E+10 Schwarz criterion 26.16346

Log likelihood −189.4558 Hannan-Quinn criter. 25.92493

F-statistic 217.4771 Durbin-Watson stat 2.138394

Prob(F-statistic) 0.000000

The joint test model passed all tests except in regards to industrial waste. There is a

high correlation between dependent and independent variables, and the model has au-tocorrelation; air and water variables follow a normal distribution with a standard ac-ceptable error.

t- Statistic Prob Probabilidad F-statistic)

R DW Resultado

Tablas (Guajarati)

2.093 0.05 19.4 0.894 - 1.828 2.172 - 3.106

Aire 21.76 0.0000 OK

Agua 61.47 0.0003 OK

Desechos 0.98 0.3480 NO

conjunto 217.47 98.86 2.13 OK

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According to values provided by Gujarati (2003), the value of acceptance must be equal to or greater than 2.093and less than 0.05 in probability. Our results thus indicate that Air and Water variables are satisfactory, but there is insufficient correlation be-tween Industrial wastes and Exports due to the high t-value (0.98). In other words, government investments to combat pollution via industrial waste in China are not adequately addressing the problem; exports produce more industrial waste than in-vestment combats it.

After testing the statistical probability Q, we confirmed that all variables are within the acceptance range for both autocorrelation and partial correlation. With this ma-thematical support, the model states that there are no symptoms of autocorrelation–the model is unbiased, efficient, and consistently linear with normal distribution.

The graph displays the following information: N = 20, 95% confidence level, 0.25 (calculated) < 7.43 (value tables), and Jarque-Bera Probability 2.72 > 0.05. Altogether, the data indicates that the model has a normal distribution (Figure 6).

Investment in industrial waste has little correlation with total exports in both the joint test and the individual events. There are than 50% of solid wastes yet unaccounted for and, although investment to combat this pollution occurs, it is yet in effective in terms of actually addressing industrial sector issues. Arguably, foreign direct invest-ment and the industrial model of China’s exports have significantly increased industrial solid waste among those sectors that generate the highest level of these wastes, includ-ing electronic products, machinery and equipment, and chemical products.

In summary, we have now confirmed that Chinese investments in combating pollu-tion have regular data except in the industrial wastes category—this indicates that Chi- nese exports are the main source of these pollutants. Statistics, however, indicate that

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Figure 6. Distribution Jarque-Bera test. Source: self-elaboration. the main problem is water contamination, so we performed another test via LS method using the following model:

Dependent Variables Independent Variable

IPIB = GDP investment

IAR = Air investment

IAG = Water investment

IDS = Industrial Waste investment

9.2. Individual Test

The model was formulated as follows:

IPIB IAR IAG IDS c= + + +

The following are the results of the individual tests:

Variable R2 P t F DW ARMA Result

Air 0.7364 0.0000 11.69 0.67 OK

Water 0.4742 0.0000 8.19 0.19 Weak

Waste 0.3468 0.0000 7.09 0.40 Weak

There is a weak relationship between the variables GDP, Water (47.42%), and Waste

(34.68%).These percentages relate to the problems identified in the descriptive statistics (Water) and the first econometric model correlation (Industrial waste). Within the econometric analysis of GDP with Air-Water-Waste variables, China’s economic policy on environmental pollution and investments appears to decline; it then is only actually able to solve Air pollution problems.

The regression equation was established as follows: GDP 98.4056144744 WATER 711.586380473 AIR

9696.76944578 WASTE 945178.7759= ∗ + ∗+ ∗ −

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Dependent Variable: GDP

Method: Least Squares

Date: 05/10/16 Time: 12:21

Sample (adjusted): 1997 2014

Included observations: 15 after adjustments

Convergence achieved after 36 iterations

Variable Coefficient Std. Error t-Statistic Prob.

WATER 407.4889 672.7532 0.605703 0.5582

AIR 764.4963 253.3390 3.017681 0.0129

WASTE 354.8014 2963.157 0.119738 0.9071

C 159744.2 796551.5 0.200545 0.8451

AR (2) −0.034794 0.582154 −0.059767 0.9535

R-squared 0.971901 Mean dependent var. 3,207,678

Adjusted R-squared 0.960661 S.D. dependent var. 2,980,805

S.E. of regression 591,214.3 Akaike info criterion 29.67895

Sum squared resid 3.50E + 12 Schwarz criterion 29.91496

Log likelihood −217.5921 Hannan-Quinn criter. 29.67643

F-statistic 86.47036 Durbin-Watson stat 1.125781

Prob (F-statistic) 0.000000

It is important to note that although overall the model yields an R2adjusted to 96.09%

(high correlation), investments in water and waste are not significant. That is to say, government efforts to address water and waste pollution are not adequate in terms of China’s pollution problem. It is necessary to revise China’s investment policy to effec-tively combat pollution. (It is also worth noting that the model contains two lags im-posed to avoid autocorrelation.)

The joint test model reflects the following indicators:

t- Statistic Prob. Prob

(F-statistic) R y R2 DW Result ARMA

Table 2.093 0.05 19.4 0.894 - 1.828 2.172 - 3.106

Air 3.01 0.01 OK

Water 0.60 0.55 NO

Indus waste 0.11 0.90 NO

Set 86.47 0.98 0.96 1.12 OK 2

Again according to Gujarati (2003), the value of acceptance must be equal to or

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greater than 2.093 and less than 0.05 in probability. The results obtained from our model tell us that the only variable that meets these assumptions is Air, with a value of 3.01 and a probability of 0.01.

Water showed a 0.6 t-value and probability of 0.55, thus placing this variable outside of the acceptable range; Waste resulted in 0.11 t-value and a probability of 0.90, likewise outside of the acceptance range. We can thus assume categorically that the Chinese government’s efforts have focused mainly on combating air pollution while failing to appropriately address either water pollution or the reduction, processing, or manage- ment of industrial waste.

In effort to confirm or reject the above statement, we checked it against the funds that the Chinese government allocated to pollution prevention in the year 2014: Air = $12,843.03 million Water = $1853.10 million Waste = $242.90 million

In other words, the percentages of total investments to combat pollution in the year 2014 were 8.34% to air, 1.20% to waste, and 0.16% to water. The total for the three items is 9.70%. In this sense, the model affirms that the Chinese government has paid relatively little attention to combating pollution. When translating these percentages to GDP, we found that only 0.15% is earmarked for this indicator as-intended to mitigate pollution: Investments to combat pollution, then, represented most none of the Chinese GDP.

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As expressed in the diagram above, if Exports is taken as a dependent variable with respect to investment in Water and Waste, there is a high dispersion of values: Statisti-cally, the standard deviation is high while the Air variable has smaller dispersion. The trend of air emission makes a 45 degree line, suggesting that there is intensive invest-ment to control air pollution—the line representing the Water variable is less steep, conversely, suggesting that investments in combating water pollution grew at a slower rate than those dedicated to combating air pollution across the timeline.

10. Conclusions

Our conclusions regarding the correlation among GDP, exports, and investment in re-ducing water, air, and industrial waste pollution can be summarized as follows.

China’s exports represent 23% of GDP with a growth rate of 26.39% annually from 1995 to 2014. There has clearly been dynamism in this sector that has enhanced eco-nomic growth across the country, and it is important to note that this 96% corresponds to finished industrial products—a sector that has a growth rate of 18% annual average.

Descriptive statistics clearly tell us that of the millions of tons of pollutants produced in China, most (95.16%) are dumped into water (Figure 5). This situation creates a striking contrast against the government’s investment in reducing water pollution, 1.85 billion USD, while the total investment made in 2014 in the three areas analyzed (air, water, and waste) was 61,438 million USD. China indeed continues to grow at 6% an-nual GDP, however, water pollution and industrial waste are still not properly cared for; the R2 model established in this study (water 47.42%; waste 36.68%) for this pur-pose, IPIB IAR IAG IDS C= + + + , indicates that the correlation indices are weak and insignificant; in short, government investment in these areas to combat pollution is demonstrably insufficient.

During the investigation, it was determined that the origin of more than 50% of solid wastes comprising the total known industrial waste was unaccounted for. This situation is serious: Not knowing precisely the final destination of these pollutants and the mag-nitude of its effects on the population represents a very urgent problem. Further, it is clear that investment in combating industrial pollution has little correlation to the country’s total exports; clearly, investment in this area is irrelevant in terms of the ac-tual conditions in this sector. In the year 2014, a total of 3526.1 thousand tons of waste (of which 2043.3 thousand tons was utilized and 450.3 thousand tons was stored) con-tained 1032.6 thousand tons (29.28% of the total) of unknown whereabouts. Alarming-ly, if this waste is continue to accumulate in the same rate, more than five billion tons of scattered industrial waste will accumulate over China in the next five years. Worse, without knowledge of the whereabouts of this waste and thereby any meaningful as-sessment of its effects on the population, this issue may pose a sizable threat to human health—particularly as a high percentage of air pollution is estimated to originate from these pollutants.

We also examined the overall investment in the environment according to a few key factors. Construction of environmental infrastructure received the highest concentra-

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tion of investment at 57%, urban gas network construction received 6%, central heating construction 8%, drainage network installation 12.5%, and the construction of green areas received 24% (Table 7).

Though the Chinese government has made important steps towards reducing pollu-tion, such as investment in heating, urban gas, and green areas, it is estimated that in-dustrial growth driven by exports have exceeded these efforts and minimized their im-pact. The government would do well to enact public policies to regulate industries re-garding the management of pollutant-laden waste.

Put simply, China invests 0.15% of its GDP into solving 70% of its environmental contaminant issues. Of this 0.15%, the Chinese government invests about 90% in air pollution and only 10% in contaminated water and industrial waste. Basically, the re-sults of this study indicate that state-level investment does little to actually address China’s pollution problem. We would argue that China needs to implement environ-mental reform to rework its environmental protection investment to ensure sustained growth. Antipollution measures for water and industrial waste must increase; taxes should likewise increase for those industries that continue to pollute. If current trends continue, the high cost of health and environmental sacrifices will surpass China’s economic growth.

This study was not without limitations. The information provided here can be con-sidered as a starting point for further research. The primary limitations are: Table 7. Decomposition of environmental investment in China 2000-2014 in millions of dollars.

Year Inv tot

Inv Indus

Inv Air

Inv Water

Inv Waste

Infrastructure Urban

gas Central heating

Urban drainage

Green areas

2000 12,260 2836 1098 1324 139 6227 856 819 1803 1730

2001 13,371 2109 795 881 226 7198 912 991 2712 1972

2002 16,518 2276 843 864 195 9534 1068 1467 3322 2894

2003 19,664 2680 1113 1056 195 12,956 1613 1761 4533 3889

2004 23,071 3722 1725 1276 274 13,786 1792 2094 4256 4342

2005 29,199 5602 2604 1635 335 15,770 1741 2692 4500 5029

2006 32,017 6038 2911 1886 228 16,406 1935 2790 4136 5353

2007 44,498 7257 3616 2576 240 19,278 2103 3021 5386 6905

2008 69,872 7680 3760 2754 279 31,811 2820 4645 9018 11,661

2009 76,969 6186 3403 2188 320 47,499 3209 6463 15,158 16,652

2010 112,718 5879 2796 1935 212 76,736 5300 8255 17,365 39,545

2011 108,944 6806 3242 2415 481 69,789 6801 9086 14,879 30,504

2012 130,800 7932 4084 2223 391 80,232 8745 12,648 14,803 37,719

2013 145,921 13,719 10,349 2016 227 84,334 9816 13,232 17,035 36,086

2014 154,031 16,049 12,843 1853 243 87,892 9233 12,274 19,240 37,617

Based on data from the national institute of statistics of China.

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1. This research is descriptive-explanatory and it provides (generally) macroeconomic variables within an econometric model and describes how they are interrelated and/ or interact with each other.

2. This study did not include a cross-sectional analysis by sector or subsector, which would have yielded more precise information regarding which was the most pollu-tant-intensive.

3. The quantitative analysis performed here provided a ratio of exports to environ-mental pollution; in this sense, it is not possible to propose public policies that help to diminish the effects of pollution though the data obtained may represent a solid basis for initiating such studies.

Reducing the volume of pollutants produced across China is a highly complex and challenging endeavor. The results described above lend themselves to a number of po-tential proposals which can be summarized as follows. 1. An industrial diagnosis identifying volumes elements that spew into the environ-

ment by industry is required. It is necessary to determine the level to which various technologies applied to various industries’ production processes are especially pol-lutant-intensive in order to invest accordingly.

2. The current legislation regarding industrial operation should be reviewed with the purpose of identifying weak points that allow such high levels of pollutant emissions on Chinese soil. These points can then be countered with robust legislation.

3. Research, innovation, and the application of newer, cleaner technologies should be determinedly promoted to reduce the quantity and volume of pollutants. There must also be a economic and environmental reform in the cost involved for public finances to encourage investment in China’s ecological future.

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